CUDALink Functions

High-level CUDALink functions like the image processing, linear algebra, and fast Fourier transforms can be used on different kernels like any other Wolfram Language function. The only difference is that the $CUDADevice variable is set to the device on which computation is performed.

Here you set image names to be taken from the dataset for ExampleData.

This allocates the seed values—note that seed evaluation needs to be performed on each worker kernel so that the random numbers are not correlated. The output memory is also allocated, computation is performed, and the result is visualized.